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Filtering by: Creator/Author Boylan, Andrew Remove constraint Creator/Author: Boylan, Andrew Publisher University of Cincinnati Remove constraint Publisher: University of Cincinnati

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  • Vocabulary Count Feature Vectors for Medical School Classifier

    Dataset thumbnail: Vocabulary Count Feature Vectors for Medical School Classifier
    Type:
    Dataset
    Description/Abstract:
    Classifier algorithms use the features (collectively known as Feature Vectors) of each item in a dataset to assess the classification to which that item belongs. In this classifier approach, each item represents one document containing the application essay combined with unstructured language describing relevant activities of a single applicant. For privacy, the full text of this document is not provided. Instead, each document is represented only by its features. The feature vector for this classifier is based on the term frequency for each of the identified terms. E.G. Doc_A contains 0 occurrences of any terms identified as family medicine vocabulary, and 10 occurrences of terms from the the non-family-medicine vocabulary.
    Creator/Author:
    Boylan, Andrew and McCabe, Erin E.
    Submitter:
    Erin E. McCabe
    Date Uploaded:
    05/14/2021
    Date Modified:
    05/14/2021
    License:
    Open Data Commons Public Domain Dedication and License (PDDL)